基于D-S证据模型的冻土区公路路基沉降监测技术

Monitoring Technology of Highway Subgrade Settlement in Permafrost Region Based on D-S Evidence Model

针对传统落锤式弯沉仪法无法大面积检测路面,沉降差大,导致监测效果不佳的问题,提出基于D-S证据模型的冻土区公路路基沉降监测技术。采用测定沉降值乘以经验系数法,计算主固结沉降和路基工后不均匀沉降数值,完成沉降监测仿真建模。通过构建等维信息模型,获取新的等维动态序列,对路基沉降进行预测。通过路基填筑、填料压实,实现路基沉降信息化监测。利用BP神经网络方法对路基监测稳定性进行鉴定,保证监测效果具有可靠性。由实验结果可知,基于沉降监测仿真建模的技术比传统落锤式弯沉仪法路基沉降监测差小3.7 cm,说明其监测效果较好。

Aiming at the problem that the traditional drop-weight deflectometer method cannot detect the pavement in a large area,and the settlement difference is large,which leads to poor monitoring effect,this study adopts the method of highway subgrade settlement monitoring technology based on D-S evidence model in permafrost region.The settlement monitoring simulation modeling was completed by multiplying the measured settlement value by the empirical coefficient to calculate the main consolidation settlement and the uneven settlement of the roadbed after construction.The subgrade settlement was predicted by building an iso-dimensional information model and obtaining new iso-dimensional dynamic sequences.The information monitoring of subgrade settlement is realized through subgrade filling and packing compaction.The BP neural network method is used to identify the stability of roadbed monitoring to ensure the reliability of the monitoring effect.The experimental results show that the traditional drop-weight deflectometer method is 3.7 cm larger than the technical subgrade settlement monitoring difference based on settlement monitoring simulation modeling,indicating that the monitoring effect of the simulation modeling technology is better.